10 resultados para Pennsylvania. Department of Internal Affairs

em DigitalCommons@The Texas Medical Center


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BACKGROUND: Given the fragmentation of outpatient care, timely follow-up of abnormal diagnostic imaging results remains a challenge. We hypothesized that an electronic medical record (EMR) that facilitates the transmission and availability of critical imaging results through either automated notification (alerting) or direct access to the primary report would eliminate this problem. METHODS: We studied critical imaging alert notifications in the outpatient setting of a tertiary care Department of Veterans Affairs facility from November 2007 to June 2008. Tracking software determined whether the alert was acknowledged (ie, health care practitioner/provider [HCP] opened the message for viewing) within 2 weeks of transmission; acknowledged alerts were considered read. We reviewed medical records and contacted HCPs to determine timely follow-up actions (eg, ordering a follow-up test or consultation) within 4 weeks of transmission. Multivariable logistic regression models accounting for clustering effect by HCPs analyzed predictors for 2 outcomes: lack of acknowledgment and lack of timely follow-up. RESULTS: Of 123 638 studies (including radiographs, computed tomographic scans, ultrasonograms, magnetic resonance images, and mammograms), 1196 images (0.97%) generated alerts; 217 (18.1%) of these were unacknowledged. Alerts had a higher risk of being unacknowledged when the ordering HCPs were trainees (odds ratio [OR], 5.58; 95% confidence interval [CI], 2.86-10.89) and when dual-alert (>1 HCP alerted) as opposed to single-alert communication was used (OR, 2.02; 95% CI, 1.22-3.36). Timely follow-up was lacking in 92 (7.7% of all alerts) and was similar for acknowledged and unacknowledged alerts (7.3% vs 9.7%; P = .22). Risk for lack of timely follow-up was higher with dual-alert communication (OR, 1.99; 95% CI, 1.06-3.48) but lower when additional verbal communication was used by the radiologist (OR, 0.12; 95% CI, 0.04-0.38). Nearly all abnormal results lacking timely follow-up at 4 weeks were eventually found to have measurable clinical impact in terms of further diagnostic testing or treatment. CONCLUSIONS: Critical imaging results may not receive timely follow-up actions even when HCPs receive and read results in an advanced, integrated electronic medical record system. A multidisciplinary approach is needed to improve patient safety in this area.

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This paper reports a comparison of three modeling strategies for the analysis of hospital mortality in a sample of general medicine inpatients in a Department of Veterans Affairs medical center. Logistic regression, a Markov chain model, and longitudinal logistic regression were evaluated on predictive performance as measured by the c-index and on accuracy of expected numbers of deaths compared to observed. The logistic regression used patient information collected at admission; the Markov model was comprised of two absorbing states for discharge and death and three transient states reflecting increasing severity of illness as measured by laboratory data collected during the hospital stay; longitudinal regression employed Generalized Estimating Equations (GEE) to model covariance structure for the repeated binary outcome. Results showed that the logistic regression predicted hospital mortality as well as the alternative methods but was limited in scope of application. The Markov chain provides insights into how day to day changes of illness severity lead to discharge or death. The longitudinal logistic regression showed that increasing illness trajectory is associated with hospital mortality. The conclusion is reached that for standard applications in modeling hospital mortality, logistic regression is adequate, but for new challenges facing health services research today, alternative methods are equally predictive, practical, and can provide new insights. ^

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Hierarchically clustered populations are often encountered in public health research, but the traditional methods used in analyzing this type of data are not always adequate. In the case of survival time data, more appropriate methods have only begun to surface in the last couple of decades. Such methods include multilevel statistical techniques which, although more complicated to implement than traditional methods, are more appropriate. ^ One population that is known to exhibit a hierarchical structure is that of patients who utilize the health care system of the Department of Veterans Affairs where patients are grouped not only by hospital, but also by geographic network (VISN). This project analyzes survival time data sets housed at the Houston Veterans Affairs Medical Center Research Department using two different Cox Proportional Hazards regression models, a traditional model and a multilevel model. VISNs that exhibit significantly higher or lower survival rates than the rest are identified separately for each model. ^ In this particular case, although there are differences in the results of the two models, it is not enough to warrant using the more complex multilevel technique. This is shown by the small estimates of variance associated with levels two and three in the multilevel Cox analysis. Much of the differences that are exhibited in identification of VISNs with high or low survival rates is attributable to computer hardware difficulties rather than to any significant improvements in the model. ^

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The premise of this study is that changes in the agency's organizational structure reflect changes in government public health policy. Based on this premise, this study tracks the changes in the organizational structure and the overall expansion of the Texas Department of Health to understand the evolution of changing public health priorities in state policy from September 1, 1946 through June 30, 1994, a period of growth and new responsibilities. It includes thirty-seven observations of organizational structure as depicted by organizational charts of the agency and/or adapted from public documents. ^ The major questions answered are, what are the changes in the organizational structure, why did they occur and, what are the policy priorities reflected in these changes in and across the various time periods. ^ The analysis of the study included a thorough review of the organizational structure of the agency for the time-span of the study, the formulation of the criteria to be used in ascertaining the changes, the delineation of the changes in the organizational structure and comparison of the observations sequentially to characterize the change, the discovery of reasons for the structural changes (financial, statutory - federal and state, social and political factors), and the determination of policy priorities for each time period and their relation to the expansion and evolution of the agency. ^ The premise that the organizational structure of the agency and the changes over time reflect government public health policy and agency expansion was found to be true. ^

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Major objectives within Healthy People 2010 include improving hypertension and mental health management of the American population. Both mental health issues and hypertension exist in the military which may decrease the health status of military personnel and diminish the ability to complete assigned missions. Some cases may be incompatible with military service even with optimum treatment. In the interest of maintaining a fit fighting force, the Department of Defense regularly conducts a survey of health related behaviors among active duty military personnel. The 2005 DoD Survey was conducted to obtain information regarding health and behavioral readiness among active duty military personnel to assess progress toward selected Healthy People 2010 objectives. ^ This study is a cross-sectional prevalence design looking at the association of hypertension treatment with mental health issues (either treatment or perceived need for treatment) within the military population sampled in the 2005 DoD Survey. There were 16,946 military personnel in the final cross-sectional sample representing 1.3 million active duty service members. The question is whether there is a significant association between the self-reported occurrence of hypertension and the self-reported occurrence of mental health issues in the 2005 DoD Survey. In addition to these variables, this survey examined the contribution of various sociodemographic, occupational, and behavioral covariates. An analysis of the demographic composition of the study variables was followed by logistic analysis, comparing outcome variables with each of the independent variables. Following univariate regression analysis, multivariate regression was performed with adjustment (for those variables with an unadjusted alpha level less than or equal to 0.25). ^ All the mental health related indicators were associated with hypertension treatment. The same relationship was maintained after multivariate adjustment. The covariates remaining as significant (p < 0.05) in the final model included gender, age, race/ethnicity and obesity. There is a need to recognize and treat co-morbid medical diagnoses among mental health patients and to improve quality of life outcomes, whether in the military population or the general population. Optimum health of the individual can be facilitated through discovery of treatable cases, to minimize disruptions of military missions, and even allow for continued military service. ^

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Objective. The purpose of this study was to examine the association of perceived stress and passing the fitness test in a cohort of Department of Defense active duty members. Reports of this association have been suggested in numerous articles. Methods. The 2005 DoD Survey of Health Related Behaviors Among Active Duty Military Personnel was used to examine the association between the participants’ perceived levels of stress from family and/or work related sources and the respondents’ last required fitness test taking into account potential confounder of the association. Measures of association were obtained from logistic regression models. Results. Participants who experienced “some” or “a lot” of stress either from work sources (OR 0.69, 95% CI: 0.58-0.87) or from personal/family sources (OR 0.70, 95% CI: 0.57-0.86) were less likely to pass the fitness test when compared to their counterparts who experienced “none” or “a little” stress. Additionally, those who reported “some” or “a lot” of stress either from work sources (OR 0.54, 95% CI: 0.41-0.70) or from personal/family sources (OR 0.54, 95% CI: 0.44-0.67) that interfered with their military duties were also less likely to pass the fitness test. The multivariate adjustment only slightly reduced the unadjusted association. Conclusions . An association exists between perceived stress levels and outcome of fitness testing. The higher the level of stress perceived, the less likely the person will be to pass the fitness test. Stress-related intervention might be useful to help the military members to achieve the level of fitness needed to perform their duties.^

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Background. The prevalence of obesity and overweight children has been an ongoing health epidemic in the US for the last several decades. The problem has consistently worsened and has disproportionately been the most prevalent among low socioeconomic status (SES) populations. Food availability in the home has been suggested to be a potential factor related to overweight and obesity, as availability is likely associated with intake. Food availability of low SES preschool aged children has not been well examined. The purpose of this study was to explore the food environment of the Harris County Department of Education (HCDE) Head Start population, and describe reported frequency of intake of particular food groups. The effect of food availability on reported intake was also examined.^ Methods. This was a cross-sectional study of secondary data analysis. Data obtained from 17 HCDE Head Start Centers was analyzed using PASW 18 Statistical Software. Demographic analyses included population, age, gender, race, parent occupation, type of home, and language spoken in the home. Descriptive statistics included reported availability of foods in the home as well as frequency of intake.^ Regression analysis examined the relationship of availability of foods on intake. The food categories included were: dark leafy green and orange vegetables, other vegetables, fruits, soda, salty snacks, and sweet snacks. For both vegetable categories reported intake of fresh, frozen, and canned vegetables were included. For the fruit category, intake of fresh, frozen, canned, and dried fruits were reported.^ Results. Results showed that 90-95% of parents reported having vegetables and fruits available in the home. However, the only significant relationship between availability and intake was for fresh fruit and dried fruit. No associations were seen among the vegetable groups. Other vegetables (bell peppers, eggplant, tomatoes, onions, iceberg lettuce, asparagus) that were frozen, approached significance for availability on intake, however once adjusted for confounders the relationship was no longer present. Among soda, salty snacks, and sweet snacks the only significant relationship was seen for soda availability and intake. Salty snacks and sweet snacks presence in the home was not a predictor of increased frequency of intake.^ Conclusions. This research supported the hypothesis that availability of foods has an impact on intake for fresh fruits, dried fruits and soda. No associations were seen for vegetables, salty snacks and sweet snacks. Additionally, most of the parents reported having fruits and vegetables in the home, but reported intakes were not meeting the Dietary Guidelines for Americans recommendations. Strengths of the study included the large sample size taken from numerous HCDE Head Start Centers. Limitations included questionable reliability of participant’s responses, ability to generalize to other populations, and the use of secondary data rather than prospectively collected data.^

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This study demonstrated that accurate, short-term forecasts of Veterans Affairs (VA) hospital utilization can be made using the Patient Treatment File (PTF), the inpatient discharge database of the VA. Accurate, short-term forecasts of two years or less can reduce required inventory levels, improve allocation of resources, and are essential for better financial management. These are all necessary achievements in an era of cost-containment.^ Six years of non-psychiatric discharge records were extracted from the PTF and used to calculate four indicators of VA hospital utilization: average length of stay, discharge rate, multi-stay rate (a measure of readmissions) and days of care provided. National and regional levels of these indicators were described and compared for fiscal year 1984 (FY84) to FY89 inclusive.^ Using the observed levels of utilization for the 48 months between FY84 and FY87, five techniques were used to forecast monthly levels of utilization for FY88 and FY89. Forecasts were compared to the observed levels of utilization for these years. Monthly forecasts were also produced for FY90 and FY91.^ Forecasts for days of care provided were not produced. Current inpatients with very long lengths of stay contribute a substantial amount of this indicator and it cannot be accurately calculated.^ During the six year period between FY84 and FY89, average length of stay declined substantially, nationally and regionally. The discharge rate was relatively stable, while the multi-stay rate increased slightly during this period. FY90 and FY91 forecasts show a continued decline in the average length of stay, while the discharge rate is forecast to decline slightly and the multi-stay rate is forecast to increase very slightly.^ Over a 24 month ahead period, all three indicators were forecast within a 10 percent average monthly error. The 12-month ahead forecast errors were slightly lower. Average length of stay was less easily forecast, while the multi-stay rate was the easiest indicator to forecast.^ No single technique performed significantly better as determined by the Mean Absolute Percent Error, a standard measure of error. However, Autoregressive Integrated Moving Average (ARIMA) models performed well overall and are recommended for short-term forecasting of VA hospital utilization. ^

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Clinical trials are often not successful because of the inability to recruit a sufficient number of patients. The Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT), the largest antihypertensive trial ever conducted, provided highly generalized results and successful recruitment of over 42,000 participants. The overall purpose of this study was to examine the association of investigator characteristics with anti-hypertensive (AHT) participant recruitment in ALLHAT. This secondary data analyses collected data from the ALLHAT investigator profile survey and related investigator characteristics to recruitment success. The sample size was 502 investigators, with recruitment data from 37,947AHT participants. Recruitment was dichotomized by categorizing all sites with recruitment numbers at or above the overall median recruitment number of 46 as "Successful Recruitment". Frequency distributions and univariate and multivariate logistic regression were conducted. When adjusting for all other factors, Hispanic ethnicity, suburban setting, Department of Veterans Affairs Medical Centers (VAMC) site type, number of clinical site staff working on the trial, study coordinator hours per week, medical conference sessions attended, the investigator's primary goal and the likelihood that a physician will convince a patient to continue on randomized treatment, have significant impacts on the recruitment success of ALLHAT investigators. Most of the ALLHAT investigators described their primary commitment as being towards their patients and not to scientific knowledge alone. However, investigators that distinguished themselves as leaders in research had greater recruitment success than investigators who were leaders in clinical practice. ALLHAT was a highly successful trial that proved that community based cardiovascular trials can be implemented on a large scale. Exploring characteristics of ALLHAT investigators provides data that can be generalized to sponsors, sites, and others interested in maximizing clinical trial recruitment numbers. Future studies should further evaluate investigator and study coordinator factors that impact cardiovascular clinical trial recruitment success.^